Visuomotor Adaptation Deficits in Patients with Essential Tremor

Essential tremor (ET) is a progressive movement disorder whose pathophysiology is not fully understood. Current evidence supports the view that the cerebellum is critically involved in the genesis of the tremor in ET. However, it is still unknown whether cerebellar dysfunction affects not only the control of current movements but also the prediction of future movements through dynamic adaptation toward a changed environment. Here, we tested the capacity of 28 patients with ET to adapt in a visuomotor adaptation task known to depend on intact cerebellar function. We found specific impairments in that task compared to age-matched healthy controls. Adaptation to the visual perturbation was disrupted in ET patients, while de-adaptation, the phase after abrupt removal of the perturbation, developed similarly to control subjects. Baseline tremor-independent motor performance was as well similar to healthy controls, indicating that adaptation deficits in ET patients were not rooted in an inability to perform goal-directed movements. There was no association between clinical severity scores of ET and early visuomotor adaptation abilities. These results provide further evidence that the cerebellum is dysfunctional in ET.

Neuronavigated Cerebellar 50 Hz tACS: Attenuation of Stimulation Effects by Motor Sequence Learning

Cerebellar transcranial alternating current stimulation (tACS) is an emerging non-invasive technique that induces electric fields to modulate cerebellar function. Although the effect of cortical tACS seems to be state-dependent, the impact of concurrent motor activation and the duration of stimulation on the effects of cerebellar tACS has not yet been examined. In our study, 20 healthy subjects received neuronavigated 50 Hz cerebellar tACS for 40 s or 20 min, each during performance using a motor sequence learning task (MSL) and at rest. We measured the motor evoked potential (MEP) before and at two time points after tACS application to assess corticospinal excitability. Additionally, we investigated the online effect of tACS on MSL. Individual electric field simulations were computed to evaluate the distribution of electric fields, showing a focal electric field in the right cerebellar hemisphere with the highest intensities in lobe VIIb, VIII and IX. Corticospinal excitability was only increased after tACS was applied for 40 s or 20 min at rest, and motor activation during tACS (MSL) cancelled this effect. In addition, performance was better (shorter reaction times) for the learned sequences after 20 min of tACS, indicating more pronounced learning under 20 min of tACS compared to tACS applied only in the first 40 s.

Motor learning is independent of effects of subthalamic deep brain stimulation on motor execution

Motor learning is defined as an improvement in performance through practice. The ability to learn new motor skills may be particularly challenged in patients with Parkinson's disease, in whom motor execution is impaired by the disease-defining motor symptoms such as bradykinesia. Subthalamic deep brain stimulation is an effective treatment in advanced Parkinson’s disease, and its beneficial effects on Parkinsonian motor symptoms and motor execution have been widely demonstrated. Much less is known about whether deep brain stimulation directly interacts with motor learning independent of modulation of motor execution.

We investigated motor sequence learning in nineteen patients with Parkinson’s disease treated with subthalamic deep brain stimulation and nineteen age-matched controls. In a cross-over design, patients performed an initial motor sequence training session with active and inactive stimulation, respectively (experiments separated by ≥ 14 days). Performance was retested after five minutes and after a 6-hour consolidation interval with active stimulation. Healthy controls performed a similar experiment once. We further investigated neural correlates underlying stimulation-related effects on motor learning by exploring the association of normative subthalamic deep brain stimulation functional connectivity profiles with stimulation-related differences in performance gains during training.

Pausing deep brain stimulation during initial training resulted in inhibition of performance gains that could have been indicative of learning at the behavioral level. Task performance improved significantly during training with active deep brain stimulation, but did not reach the level of learning dynamics of healthy controls. Importantly, task performance after the 6-hour consolidation interval was similar across patients with Parkinson’s disease independent of whether the initial training session had been performed with active or inactive deep brain stimulation. This indicates that early learning and subsequent consolidation were relatively intact despite severe impairments of motor execution during training with inactive deep brain stimulation. Normative connectivity analyses revealed plausible and significant connectivity of volumes of tissue activated by deep brain stimulation with several cortical areas. However, no specific connectivity profiles were associated with stimulation-dependent differences in learning during initial training.

Our results show that motor learning in Parkinson’s disease is independent of modulation of motor execution by subthalamic deep brain stimulation. This indicates an important role of the subthalamic nucleus in regulating general motor execution, whereas its role in motor learning appears negligible. Because longer-term outcomes were independent of performance gains during initial training, patients with Parkinson’s disease may not need to wait for an optimal motor state to practice new motor skills.

Classification of EEG signals reveals a focal aftereffect of 10 Hz motor cortex transcranial alternating current stimulation

Transcranial alternating current stimulation (tACS) modulates oscillations in a frequency- and location-specific manner and affects cognitive and motor functions. This effect appears during stimulation as well as “offline,” following stimulation, presumably reflecting neuroplasticity. Whether tACS produces long-lasting aftereffects that are physiologically meaningful, is still of current debate. Thus, for tACS to serve as a reliable method for modulating activity within neural networks, it is important to first establish whether “offline” aftereffects are robust and reliable. In this study, we employed a novel machine-learning approach to detect signatures of neuroplasticity following 10 Hz tACS to two critical nodes of the motor network: left motor cortex (lMC) and right cerebellum (rCB). To this end, we trained a classifier to distinguish between signals following lMC-tACS, rCB-tACS and sham. Our results demonstrate better classification of EEG signals in both theta (θ, 4 Hz-8 Hz) and alpha (α, 8 Hz-13 Hz) frequency bands to lMC-tACS compared to rCB-tACS/sham, at lMC-tACS stimulation location. Source reconstruction allocated these effects to premotor cortex. Stronger correlation between classification accuracies in θ and α in lMC-tACS suggested an association between θ and α efffects. Together these results suggest that EEG signals over premotor cortex contains unique signatures of neuroplasticity following 10 Hz motor cortex tACS.

Effective connectivity underlying reward-based executive control

Motivational influences on cognitive control play an important role in shaping human behavior. Cognitive facilitation through motivators such as prospective reward or punishment is thought to depend on regions from the dopaminergic mesocortical network, primarily the ventral tegmental area (VTA), inferior frontal junction (IFJ), and anterior cingulate cortex (ACC). However, how interactions between these regions relate to motivated control remains elusive. In the present functional magnetic resonance imaging study, we used dynamic causal modeling (DCM) to investigate effective connectivity between left IFJ, ACC, and VTA in a task-switching paradigm comprising three distinct motivational conditions (prospective monetary reward or punishment and a control condition). We found that while prospective punishment significantly facilitated switching between tasks on a behavioral level, interactions between IFJ, ACC, and VTA were characterized by modulations through prospective reward but not punishment. Our DCM results show that IFJ and VTA modulate ACC activity in parallel rather than by interaction to serve task demands in reward-based cognitive control. Our findings further demonstrate that prospective reward and punishment differentially affect neural control mechanisms to initiate decision-making.

Alpha oscillations modulate premotor-cerebellar connectivity in motor learning: Insights from transcranial alternating current stimulation

Alpha oscillations (8-13 Hz) have been suggested to play an important role in dynamic neural processes underlying learning and memory. The goal of this study was to scrutinize the role of alpha oscillations in communication within a cortico-cerebellar network implicated in motor sequence learning. To this end, we conducted two EEG experiments using a serial reaction time task. In the first experiment, we explored changes in alpha power and cross-channel alpha coherence as subjects learned a motor sequence. We found a gradual decrease in spectral alpha power over left premotor cortex (PMC) and sensorimotor cortex (SM1) during learning blocks. In addition, alpha coherence between left PMC/SM1 and left cerebellar crus I was specifically decreased during sequence learning, possibly reflecting a functional decoupling in the broader motor learning network. In the second experiment in a different cohort, we applied 10Hz transcranial alternating current stimulation (tACS), a method shown to entrain local oscillatory activity, to left M1 (lM1) and right cerebellum (rCB) during sequence learning. We observed a tendency for diminished learning following rCB tACS compared to sham, but not following lM1 tACS. Learning-related alpha power following rCB tACS was increased in left PMC, possibly reflecting increase in local inhibitory neural activity. Importantly, learning-specific alpha coherence between left PMC and right cerebellar lobule VIIb was enhanced following rCB tACS. These findings provide strong evidence for a causal role of alpha oscillations in controlling information transfer in a premotor-cerebellar loop during motor sequence learning. Our findings are consistent with a model in which sequence learning may be impaired by enhancing premotor cortical alpha oscillation via external modulation of cerebellar oscillations.

Abnormal effective connectivity in the sensory network in writer's cramp

BACKGROUND

Writer's cramp (WC), a task specific form of dystonia, is considered to be a motor network disorder, but abnormal sensory tactile processing has also been acknowledged. The sensory spatial discrimination threshold (SDT) can be determined with a spatial acuity test (JVP domes). In addition to increased SDT, patients with WC exhibited dysfunctional sensory processing in the sensory cortex, insula, basal ganglia and cerebellum in a functional magnetic resonance imaging (fMRI) study while performing the spatial acuity test.

OBJECTIVES

To assess whether effective connectivity (EC) in the sensory network including cortical, basal ganglia, thalamic and cerebellar regions of interest in WC patients is abnormal.

METHODS

We used fMRI and applied a block design, while 19 WC patients and 13 age-matched healthy controls performed a spatial discrimination task. Before we assessed EC using dynamic causal modelling, we compared three model structures based on the current literature. We enclosed regions of interest that are established for sensory processing during right hand stimulation: Left thalamus, somatosensory, parietal and insular cortex, posterior putamen, and right cerebellum.

RESULTS

The EC analysis revealed task-dependent decreased unidirectional connectivity between the insula and the posterior putamen. The connectivity involving the primary sensory cortex, parietal cortex and cerebellum were not abnormal in WC. The two groups showed no differences in their behavioural data.

CONCLUSIONS

Perception and integration of sensory information requires the exchange of information between the insula cortex and the putamen, a sensory process that was disturbed in WC patients.

Motor Sequence Learning Deficits in Idiopathic Parkinson's Disease Are Associated With Increased Substantia Nigra Activity

Previous studies have shown that persons with Parkinson’s disease (pwPD) share specific deficits in learning new sequential movements, but the neural substrates of this impairment remain unclear. In addition, the degree to which striatal dopaminergic denervation in PD affects the cortico-striato-thalamo-cerebellar motor learning network remains unknown. We aimed to answer these questions using fMRI in 16 pwPD and 16 healthy age-matched control subjects while they performed an implicit motor sequence learning task. While learning was absent in both pwPD and controls assessed with reaction time differences between sequential and random trials, larger error-rates during the latter suggest that at least some of the complex sequence was encoded. Moreover, we found that while healthy controls could improve general task performance indexed by decreased reaction times across both sequence and random blocks, pwPD could not, suggesting disease-specific deficits in learning of stimulus-response associations. Using fMRI, we found that this effect in pwPD was correlated with decreased activity in the hippocampus over time. Importantly, activity in the substantia nigra (SN) and adjacent bilateral midbrain was specifically increased during sequence learning in pwPD compared to healthy controls, and significantly correlated with sequence-specific learning deficits. As increased SN activity was also associated (on trend) with higher doses of dopaminergic medication as well as disease duration, the results suggest that learning deficits in PD are associated with disease progression, indexing an increased drive to recruit dopaminergic neurons in the SN, however, unsuccessfully. Finally, there were no differences between pwPD and controls in task modulation of the cortico-striato-thalamo-cerebellar network. However, a restricted nigral-striatal model showed that negative modulation of SN to putamen connection was larger in pwPD compared to controls during random trials, while no differences between the groups were found during sequence learning. We speculate that learning-specific SN recruitment leads to a relative increase in SN- > putamen connectivity, which returns to a pathological reduced state when no learning takes place.

Mini-review: The Role of the Cerebellum in Visuomotor Adaptation

The incredible capability of the brain to quickly alter performance in response to ever-changing environment is rooted in the process of adaptation. The core aspect of adaptation is to fit an existing motor program to altered conditions. Adaptation to a visuomotor rotation or an external force has been well established as tools to study the mechanisms underlying sensorimotor adaptation. In this mini-review, we summarize recent findings from the field of visuomotor adaptation. We focus on the idea that the cerebellum plays a central role in the process of visuomotor adaptation and that interactions with cortical structures, in particular, the premotor cortex and the parietal cortex, may be crucial for this process. To this end, we cover a range of methodologies used in the literature that link cerebellar functions and visuomotor adaptation; behavioral studies in cerebellar lesion patients, neuroimaging and non-invasive stimulation approaches. The mini-review is organized as follows: first, we provide evidence that sensory prediction errors (SPE) in visuomotor adaptation rely on the cerebellum based on behavioral studies in cerebellar patients. Second, we summarize structural and functional imaging studies that provide insight into spatial localization as well as visuomotor adaptation dynamics in the cerebellum. Third, we discuss premotor — cerebellar interactions and how these may underlie visuomotor adaptation. And finally, we provide evidence from transcranial direct current and magnetic stimulation studies that link cerebellar activity, beyond correlational relationships, to visuomotor adaptation .

Cerebellar rTMS and PAS effectively induce cerebellar plasticity

Non-invasive brain stimulation techniques including repetitive transcranial magnetic stimulation (rTMS), continuous theta-burst stimulation (cTBS), paired associative stimulation (PAS), and transcranial direct current stimulation (tDCS) have been applied over the cerebellum to induce plasticity and gain insights into the interaction of the cerebellum with neo-cortical structures including the motor cortex. We compared the effects of 1 Hz rTMS, cTBS, PAS and tDCS given over the cerebellum on motor cortical excitability and interactions between the cerebellum and dorsal premotor cortex / primary motor cortex in two within subject designs in healthy controls. In experiment 1, rTMS, cTBS, PAS, and tDCS were applied over the cerebellum in 20 healthy subjects. In experiment 2, rTMS and PAS were compared to sham conditions in another group of 20 healthy subjects. In experiment 1, PAS reduced cortical excitability determined by motor evoked potentials (MEP) amplitudes, whereas rTMS increased motor thresholds and facilitated dorsal premotor-motor and cerebellum-motor cortex interactions. TDCS and cTBS had no significant effects. In experiment 2, MEP amplitudes increased after rTMS and motor thresholds following PAS. Analysis of all participants who received rTMS and PAS showed that MEP amplitudes were reduced after PAS and increased following rTMS. rTMS also caused facilitation of dorsal premotor-motor cortex and cerebellum-motor cortex interactions. In summary, cerebellar 1 Hz rTMS and PAS can effectively induce plasticity in cerebello-(premotor)-motor pathways provided larger samples are studied.

Cerebello-striatal interaction mediates effects of subthalamic nucleus deep brain stimulation in Parkinson's disease

BACKGROUND

In Parkinson's disease (PD), dopamine replacement therapy (DRT) enhances the effective connectivity of the prefrontal cortex (PFC) and supplementary motor area (SMA). The clinical effects of deep brain stimulation (DBS) of the subthalamic nucleus (STN) go beyond DRT effects including highly beneficial tremor suppression.

OBJECTIVES

Here, we aimed to determine DBS-related changes of a motor network using resting state fMRI in PD patients with chronic STN DBS.

METHODS

In a repeated-measurement design, 26 medicated PD patients (60.9 years (SD 8.9)) were investigated using resting state fMRI while bipolar STN stimulation was (i) active or (ii) switched off, and dynamic causal modelling was subsequently performed.

RESULTS

DBS improved the MDS-UPDRS-III score by 26.4% (DBS ON/Med ON vs. DBS OFF/Med ON). Active stimulation resulted in an increased effective connectivity from cerebellum to putamen (p = 0.00118). In addition, there was a stronger coupling from PFC to cerebellum (p = 0.021), as well as from cerebellum to SMA (p = 0.043) on an uncorrected level. Coupling strength from PFC to cerebellum correlated with the DBS-related change of the resting tremor subscore (r = 0.54, p = 0.031). Self-connections increased as a function of DBS in the right PFC, PMC, SMA, M1, thalamus and left cerebellum.

CONCLUSIONS

DBS-related improvement of Parkinsonian signs appears to be driven by an interaction between the cerebellum and the putamen. Resting tremor suppression may be related to an enhanced prefronto-cerebellar network. Activation of the mesial premotor loop (PFC-SMA) as seen in DRT may thus be secondary due to the primary modulation of cerebellar networks.

Ready for change: Oscillatory mechanisms of proactive motor control

Proactive motor control is a preparatory mechanism facilitating upcoming action inhibition or adaptation. Previous studies investigating proactive motor control mostly focused on response inhibition, as in the classical go-nogo or stop-signal tasks. However, everyday life rarely calls for the complete suppression of actions without subsequent behavioral adjustment. Therefore, we conducted a modified cued go-nogo-change task, in which cues indicated whether participants might have to change to an alternative action or inhibit the response to an upcoming target. Based on the dual-mechanisms of control framework and using electroencephalography (EEG), we investigated the role of the sensorimotor cortex and of prefrontal regions in preparing to change and cancel motor responses. We focused on mu and beta power over sensorimotor cortex ipsi- and contralateral to an automatic motor response and on prefrontal beta power. Over ipsilateral sensorimotor cortex, mu and beta power was relatively decreased when anticipating to change or inhibit the automatic motor behavior. Moreover, alpha phase coupling between ipsilateral motor cortex and prefrontal areas decreased when preparing to change, suggesting a decoupling of sensorimotor regions from prefrontal control. When the standard motor action actually had to be changed, prefrontal beta power increased, reflecting enhanced cognitive control. Our data highlight the role of the ipsilateral motor cortex in preparing to inhibit and change upcoming motor actions. Here, especially mu power and phase coupling seem to be critical to guide upcoming behavior.

Cerebellar degeneration affects cortico-cortical connectivity in motor learning networks

The cerebellum plays an important role in motor learning as part of a cortico-striato-cerebellar network. Patients with cerebellar degeneration typically show impairments in different aspects of motor learning, including implicit motor sequence learning. How cerebellar dysfunction affects interactions in this cortico-striato-cerebellar network is poorly understood. The present study investigated the effect of cerebellar degeneration on activity in causal interactions between cortical and subcortical regions involved in motor learning. We found that cerebellar patients showed learning-related increase in activity in two regions known to be involved in learning and memory, namely parahippocampal cortex and cerebellar Crus I. The cerebellar activity increase was observed in non-learners of the patient group whereas learners showed an activity decrease. Dynamic causal modeling analysis revealed that modulation of M1 to cerebellum and putamen to cerebellum connections were significantly more negative for sequence compared to random blocks in controls, replicating our previous results, and did not differ in patients. In addition, a separate analysis revealed a similar effect in connections from SMA and PMC to M1 bilaterally. Again, neural network changes were associated with learning performance in patients. Specifically, learners showed a negative modulation from right SMA to right M1 that was similar to controls, whereas this effect was close to zero in non-learners. These results highlight the role of cerebellum in motor learning and demonstrate the functional role cerebellum plays as part of the cortico-striato-cerebellar network.

Temporal Dynamics of Proactive and Reactive Motor Inhibition

Proactive motor inhibition refers to endogenous preparatory mechanisms facilitating action inhibition, whereas reactive motor inhibition is considered to be a sudden stopping process triggered by external signals. Previous studies were inconclusive about the temporal dynamics of involved neurocognitive processes during proactive and reactive motor control. Using electroencephalography (EEG), we investigated the time-course of proactive and reactive inhibition, measuring event-related oscillations and event-related potentials (ERPs). Participants performed in a cued go/nogo paradigm with cues indicating whether the motor response might or might not have to be inhibited. Based on the dual mechanisms of control (DMC) framework by Braver, we investigated the role of attentional effects, motor preparation in the sensorimotor cortex and prefrontal cognitive control mechanisms, separating effects before and after target onset. In the cue-target interval, proactive motor inhibition was associated with increased attention, reflected in reduced visual alpha power and an increased contingent negative variation (CNV). At the same time, motor inhibition was modulated by reduced sensorimotor beta power. After target onset, proactive inhibition resulted in an increased N1, indicating allocation of attention towards relevant stimuli, increased prefrontal beta power and a modulation of sensorimotor mu activity. As in previous studies, reactive stopping of motor actions was associated with increased prefrontal beta power and increased sensorimotor beta activity. The results stress the relevance of attentional mechanisms for proactive inhibition and speak for different neurocognitive mechanisms being involved in the early preparation for and in later implementation of motor inhibition.

Reduced alpha-gamma phase amplitude coupling over right parietal cortex is associated with implicit visuomotor sequence learning

Implicit visuomotor sequence learning is important for our daily life, e.g., when writing or playing an instrument. Previous research identified a network of cortical regions that is relevant for motor sequence learning, namely primary motor cortex, premotor cortex, superior parietal cortex, and subcortical regions, including basal ganglia and cerebellum. Here, we investigated learning-related changes in oscillatory activity (theta, alpha and gamma power) and cross-frequency interactions (theta- and alpha-gamma phase-amplitude coupling) within cortical regions during sensorimotor memory formation. EEG was recorded from a large group of participants (n=73) performing the serial reaction time task (SRTT). Posterior parietal alpha power was larger early-on during sequence learning and smaller in later sessions. Alpha/low-gamma (8-13Hz and 30-48Hz) phase-amplitude coupling (PAC) was significantly smaller during sequence learning over right superior parietal cortex and frontal cortex. During the transition from sequential stimuli to random stimuli, participants made more errors, indicating that they still implicitly attempted to implement the learned motor sequence. At the same time, alpha/low-gamma phase-amplitude coupling was found to be smaller during the transition relative to later random trials. Our results show that learning and implementing a learned motor sequence reduces alpha/low-gamma PAC over parietal and frontal cortex. Fronto-parietal alpha/low-gamma PAC might be relevant for visuomotor mapping which becomes less relevant once the motor sequence has been encoded.

Frontal and motor cortex contributions to response inhibition: evidence from electrocorticography

Changes in the environment require rapid modification or inhibition of ongoing behavior. We used the stop-signal paradigm and intracranial recordings to investigate response preparation, inhibition, and monitoring of task-relevant information. Electrocorticographic data were recorded in eight patients with electrodes covering frontal, temporal, and parietal cortex, and time-frequency analysis was used to examine power differences in the beta (13-30 Hz) and high-gamma bands (60-180 Hz). Over motor cortex, beta power decreased, and high-gamma power increased during motor preparation for both go trials (Go) and unsuccessful stops (US). For successful stops (SS), beta increased, and high-gamma was reduced, indexing the cancellation of the prepared response. In the middle frontal gyrus (MFG), stop signals elicited a transient high-gamma increase. The MFG response occurred before the estimated stop-signal reaction time but did not distinguish between SS and US trials, likely signaling attention to the salient stop stimulus. A postresponse high-gamma increase in MFG was stronger for US compared with SS and absent in Go, supporting a role in behavior monitoring. These results provide evidence for differential contributions of frontal subregions to response inhibition, including motor preparation and inhibitory control in motor cortex and cognitive control and action evaluation in lateral prefrontal cortex.